Nur Shlapobersky + Sage Voorhees
SES 5394: Travel Behavior and Forecasting
Spring Semester 2023
Oklahoma City at a Glance
Figure 1: Sketch of Oklahoma City boundaries and interstate highways.
Oklahoma City is the capital of Oklahoma and the largest city in the state. Three major interstates–I-35, I-40, and I-44 all pass through OKC. As of the 2020 Census, the OKC Metro area is majority white, with a population just shy of 1.5 million people.1 2020 Census and 2021 American Community Survey
Race
Percent of Population
White
62%
African American
10%
Native American
3%
Asian
3%
Multi-racial
8%
Other
1%
–
–
Hispanic
14%
Some well-known neighborhoods in OKC include
Figure 2: The Bricktown neighborhood.
Downtown
Bricktown - an entertainment district
Deep Deuce - a residential, formerly African American neighborhood
The Arts District
Film Row
Midtown
Automobile Alley
Plaza District
Cottage District
Uptown
Asian District
Paseo Arts District
Crown-Heights-Edgemere Heights
Western Avenue Corridor
39th Street Enclave
Elements of the Model
Figure 3: Number of households by census tract
Transit Analysis Zones
Our transportation analysis looks at 419 transit analysis zones across 7 counties, each corresponding to a census tract. In Figure 3 we can see that Oklahoma City follows a typical greater metropolitan area pattern with a dense and active urban core, surrounded by suburbs and rural areas. The
Road Network
The longest distance between zones by car was just over 3 hours and 15 minutes (190.5 minutes). The shortest distance was half a minute (0.5 minutes). The average distance between TAZ centroids is roughly 30 minutes (30.7), the median time is around 25 minutes (25.6 minutes). Roads highlighted in red in Figure 4 were modeled as two-way rural roads.
Figure 4:
The modeled Oklahoma City road network.
Public Transit Network
Figure 5: Full county map with public transit.
The OKC Transit network is composed of 651 miles of bus routes, across 30 different bus lines. The map below shows the bus network in detail, and in the context of the whole city. Of our 419 transit analysis zones for OKC metro area, the transit network connects only 135 of those zones, with the longest travel time between zones being just over 3 hours and 15 minutes (190.5 minutes). The shortest distance was half a minute (0.5 minutes). The average distance between centroids is roughly 30 minutes (30.7). The median time between centroids was around 25 minutes (25.6 minutes). The public transit is fully contained in 3 of the 7 counties that make up the OKC statistical area.
Figure 6: The public transit network in Oklahoma City.
Travel Times
Using the networks we created, we generated travel time skims which provide travel times between every TAZ. By selecting a subset we can map every zone’s travel time by car to the University of Oklahoma, as in Figure 5.
Figure 7: Travel time by car from the University of Oklahoma
As well as the travel time by bus from the University to other zones, as in Figure 6 (note that many are grayed out because they cannot be reached by bus).
TODO: Something in this data isn’t right
Figure 8: Public transit travel time to the University of Oklahoma
Accessibility
Accessibility is a measure of how many destination travelers can reach within a perceived reasonable time using transportation modes available to them. Put an alternative, and slightly more mathematical way:
We determine accessibility based on the network skims mentioned earlier and employment data. Travel times are used in a decay function to scale the “worth” of each opportunity, and these are all summed together to determine the accessibility score. See Appendix B for more information.
Accessibility by Car
Car access is distributed as is typical for a metropolitan area: the downtown, being both dense and centrally located, has higher scores than the outlying areas.
Figure 9: Car accessibility scores for each zone
While they don’t necessarily represent a large percent of the land area, there are many of those downtown high-scoring zones because they are smaller, and this is what forms the right peak in the distribution shown in Figure 10. The left peak represents the outlying rural zones.
Figure 10: Distribution of zone accessibility scores
Accessibility by Transit
Transit in Oklahoma City is quite limited to the areas in and around Downtown and the University campus. The bus lines between the two areas notably bypass most of the zones in between, creating the two island-like regions in Figure 11. Taking a look at the linear scale accessibility map, we can see that the majority of those zones have very similar low scores. There are just a few outliers with much higher accessibility scores due to the proximity of transit hubs where many of the bus lines meet.
Figure 11: Transit accessibility scores for each zone (on a log scale and a linear scale)
Those outliers can also be seen in 12 at the far right tail of the distribution.
Figure 12: Distribution of zone accessibility scores
Trip Attractions and Trip Productions
Estimating Productions and Attractions
To generate Trip Attractions and Trip Productions for each transit analysis zones, we broke up trip types into three main categories.
Home Based Work: Travel between work and home
Home Based Other: Travel between home and places other than a workplace
Non-Home Based: Travel that does not start or end at home
To generate our trip attractions and productions we conducted a linear regression using factors present in both the NHTS2 National Household Travel Survey (NHTS) from 2017 and the ACS.
We used:
Median Income (Continuous)
Whether or not the household had a vehicle (yes, no)
Household size (1 person, 2 people, 3 people, 4 or more people)
Whether or not the household had kids (yes, no)
We had a very low R-Squared value in our regressions ranging from .124 to .129. In our regressions, only household size and presence of kids was statistically significant. The resulting trips by type were as follows:
Trip Type
Total Trips
Home Based Work
124,464
Home Based Other
1,392,300
Non Home Based
1,618,000
Figure 13: Home Based Other, Trip Productions and Attractions
Figure 14: Non-Home Based, Trip Productions and Attractions
We also used NHTS data to examine mode share in OKC based on various trip types.
Fig 14: Mode Share OKC Metro Area
Fig 15: Mode Share and Trip Purpose
Fig 16: Mode Share and Trip Purpose Detail
Appendix
A: Methodology and Sources
Demographics and Land Use Data
For data about the population density, income, household size, and vehicle availability of we used 5-year Sample American Community Survey (ACS) Data from 2021. For information about the land use and employment we used Longitudinal Employer Household Dynamics (LEHD). For geographic boundaries we used census data.
Road Network
To generate the Road Network we used data pulled from Open Street Map, downloaded through the service https://extract.bbbike.org/. We included in our road network all road segments labeled as motorways, motorway_links, secondary, tertiary, trunks or unclassified roads. We decided to include the unclassified roads when we realized that major roads including US-77, US-62 were not included in motorways. Adding in unclassified roads also brought back in “boulevards,” such as Oklahoma City Boulevard and North Lincoln Boulevard. Our assumption is that since the original data did not label any roads as “primary,” many roads that would have been considered primary were instead labeled as unclassified.We then began to generate a transit skim using the software Transcad.
Public Transportation Network
In this model we used General Transit Feed Specification (GTFS) data pulled from Oklahoma City EMBARK’s GTFS feed.
B: Assumptions
Road Network
All primary and secondary roads in rural areas are two-way roads even if coded as one-way roads in the OSM data. This assumption was based on cross-referencing against satellite images that indicated roads had bi-directional traffic despite being coded as one-ways in OSM. We identified rural areas by looking at the network and selecting areas that had large, mostly rectangular Transit Area Zones (TAZs). See Figure 3 for an image of primary or secondary road segments that we treated as rural two-ways.
We made the following speed assumptions:
Unclassified road speeds are 30 mph
Motorways are 60 mph
Primary are 60 mph
Secondary are 40 mph
Tertiary are 30 mph
Centroid Connectors are 15.
In our model we assumed that centroid connectors could model residential roads in each TAZ. In our model, centroid connectors can be up to 25 miles long, but must connect to a road no more than .1 miles outside of the zone boundary. Each centroid could have up to 7 centroid connectors.
Transit Network
The maximum initial wait time for a public transit trip was 15 minutes.
The walk speed for a traveler is 2.8 miles per hour.
Buses move at 30 miles per hour.
Centroid connectors could be a maximum of 0.5 miles long.
Accessibility Metrics
We are weighting the portion of time spent waiting for a bus or train as 2.5 times the in-vehicle travel time (IVTT)
We are using a logistic decay function with an inflection point of 25 and standard deviation of 5
C: Supplemental Visualizations
Census and Employment Data
Figure 15: Employment is concentrated in the downtown area. Employment information is not available for many of our Transit Analysis Zones
Figure 16: Majority of employment in OKC metro area is in the service industry.
Fig A2: Majority of employment in OKC metro area is in the service industry
Fig A3: Employment + Activity Density is greatest in downtown OKC
Fig A4: The majoirty of census tracts have fewer than 100 households with no cars. But some tracts have more than 500 households with no vehicles.
Figure 17: Vehicle Ownership Dot Density Map
Figure 18: Highest income neighborhoods are north of downtown.
Figure 19: Census tracts by income, population density, and # of adults Living with their parents.
Figure 2: The Bricktown neighborhood.
Figure 3: Number of households by census tract
Figure 5: Full county map with public transit.
